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Le contexte incertain des marchés actuels a contribué au développement des systèmes manufacturiers, donnant lieu à des systèmes ayant des principes et des fonctionnalités multiples, qui essayent de répondre aux exigences changeantes. Les systèmes manufacturiers reconfigurables (RMS) constituent une classe des systèmes où les machines, les composants des machines ainsi que le système de manutention peuvent être ajoutés, modifiés, supprimés ou échangés selon les besoins de la production. Un RMS combine le haut débit des systèmes manufacturiers dédiés avec la flexibilité des systèmes flexibles. Le principal composant d'un RMS est la machine reconfigurable (RMT) qui possède une structure qui permet sa reconfiguration. Nous consacrons ce travail au problème de génération des plannings de fabrication dans un RMS, en exploitant au mieux les hauts degrés de reconfigurabilité des RMTs pour proposer des plannings efficaces. Trois problèmes liés à la fonction de génération des plannings de fabrication sont considérés : (1) la génération des process plans dans un cas unitaire où nous avons adaptés des techniques d'optimisation multicritère (NSGA-II et AMOSA), (2) la génération des process plans dans le cas multiunité où une optimisation basée sur la simulation a été adaptée, et (3) l'intégration des fonctions de génération des process plans avec l'ordonnancement où nous avons développé une nouvelle heuristique permettant d'effectuer cette intégration Toutes les approches proposées ont été validées par des expériences numériques, démontrant leur applicabilité et efficacité / The uncertain context of current markets has contributed to the development of manufacturing systems, resulting in systems with different features and principles, trying to meet the changing market demands. Reconfigurable manufacturing system (RMS) is a recent class of systems where machines, machine components and the handling system can be added, modified, deleted or exchanged according to the production needs. RMS combines the high throughput of dedicated manufacturing systems with the customizability of flexible systems. The main component of an RMS is the reconfigurable machine (RMT: Reconfigurable Machine Tool) which has a structure that allows reconfiguration. We focus in this work on CAPP (Computer-Aided Process Planning) to generate effective the process plans in an RMS that take advantage of the high degree of RMT reconfigurability Three problems associated with the function process planning are discussed: (1) the generation of process plans for a single-unit case, where we adapted multi-criteria optimization techniques (NSGA-II, AMOSA) (2) the generation of process plans in the multi-unit case, where we developed simulation based optimization technique, and (3) the integration of process planning and scheduling functions, where we developed a new heuristic aiming to achieve this integration. All the proposed approaches have been validated by numerical experiments, demonstrating their applicability and effectiveness

The objective of the cellular manufacturing is to simplify the management of the manufacturing industries. In regrouping the production of different parts into clusters, the management of the manufacturing is reduced to manage different small entities. One of the most important problems in the cellular manufacturing is the design of these entities called cells. These cells represent a cluster of machines that can be dedicated to the production of one or several parts. The ideal design of a cellular manufacturing is to make these cells totally independent from one another, i.e. that each part is dedicated to only one cell (i.e. if it can be achieved completely inside this cell). The reality is a little more complex. Once the cells are created, there exists still some traffic between them. This traffic corresponds to a transfer of a part between two machines belonging to different cells. The final objective is to reduce this traffic between the cells (called inter-cellular traffic). Different methods exist to produce these cells and dedicated them to parts. To create independent cells, the choice can be done between different ways to produce each part. Two interdependent problems must be solved: • the allocation of each operation on a machine: each part is defined by one or several sequences of operations and each of them can be achieved by a set of machines. A final sequence of machines must be chosen to produce each part. • the grouping of each machine in cells producing traffic inside and outside the cells. In function of the solution to the first problem, different clusters will be created to minimise the inter-cellular traffic. In this thesis, an original method based on the grouping genetic algorithm (Gga) is proposed to solve simultaneously these two interdependent problems. The efficiency of the method is highlighted compared to the methods based on two integrated algorithms or heuristics. Indeed, to form these cells of machines with the allocation of operations on the machines, the used methods permitting to solve large scale problems are generally composed by two nested algorithms. The main one calls the secondary one to complete the first part of the solution. The application domain goes beyond the manufacturing industry and can for example be applied to the design of the electronic systems as explained in the future research.

The objective of the cellular manufacturing is to simplify the management of the<p>manufacturing industries. In regrouping the production of different parts into clusters,<p>the management of the manufacturing is reduced to manage different small<p>entities. One of the most important problems in the cellular manufacturing is the<p>design of these entities called cells. These cells represent a cluster of machines that<p>can be dedicated to the production of one or several parts. The ideal design of a<p>cellular manufacturing is to make these cells totally independent from one another,<p>i.e. that each part is dedicated to only one cell (i.e. if it can be achieved completely<p>inside this cell). The reality is a little more complex. Once the cells are created,<p>there exists still some traffic between them. This traffic corresponds to a transfer of<p>a part between two machines belonging to different cells. The final objective is to<p>reduce this traffic between the cells (called inter-cellular traffic).<p>Different methods exist to produce these cells and dedicated them to parts. To<p>create independent cells, the choice can be done between different ways to produce<p>each part. Two interdependent problems must be solved:<p>• the allocation of each operation on a machine: each part is defined by one or<p>several sequences of operations and each of them can be achieved by a set of<p>machines. A final sequence of machines must be chosen to produce each part.<p>• the grouping of each machine in cells producing traffic inside and outside the<p>cells.<p>In function of the solution to the first problem, different clusters will be created to<p>minimise the inter-cellular traffic.<p>In this thesis, an original method based on the grouping genetic algorithm (Gga)<p>is proposed to solve simultaneously these two interdependent problems. The efficiency<p>of the method is highlighted compared to the methods based on two integrated algorithms<p>or heuristics. Indeed, to form these cells of machines with the allocation<p>of operations on the machines, the used methods permitting to solve large scale<p>problems are generally composed by two nested algorithms. The main one calls the<p>secondary one to complete the first part of the solution. The application domain goes<p>beyond the manufacturing industry and can for example be applied to the design of<p>the electronic systems as explained in the future research.<p> / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

This thesis presents methods for simplifying the use of multi-agent systems in Plug &amp; Produce. The demand for customized products and low volume production is constantly increasing. The industry has for many years used dedicated manufacturing systems where it is difficult and expensive to adapt to new product designs. Instead, factories are forced to use human workers for certain tasks that demand high flexibility and rapid adaption for new product designs. Several solutions have been proposed over the years to create highly flexible automation systems that automatically handles rapid adaption for new products. A concept called Plug &amp; Produce aims at creating a system where resources and parts can be added in minutes rather than days in dedicated systems. One promising solution for implementing Plug &amp; Produce is the distributed approach called multi-agent systems, where each resource and part get its own controller that communicates with each other to reach manufacturing goals. The idea is that the system automatically handles the adaption for new products. However, still today the use of such systems is extremely limited in the industry. One reason is the lack of mature multi-agent systems that are easy to use and that hides the complexity of the underlying agent system from the users. This is a huge problem since these systems tend to be more complex than traditional approaches. Thus, this thesis focuses on simplifying the use of multi-agent systems by proposing various methods for bringing the multi-agent technology for Plug &amp; Produce closer to the industry. / Denna avhandling presenterar metoder för att förenkla användningen av multiagent-system för Plug &amp; Produce. Efterfrågan på kundanpassade produkter och lågvolymproduktion ökar ständigt. Industrin har under många år använt sig avdedikerade tillverkningssystem som gör det både svårt och dyrt att anpassa sig till nya produktdesigner. Istället tvingas fabriker att antälla onödigt många operatörer för vissa arbetsuppgifter där det krävs hög flexibilitet och snabb anpassning till nya produktdesigner. Flera lösningar har föreslagits under åren för att skapa flexibla automatiseringssystem som automatiskt hanterar snabb omställning till nya produkter. Ett koncept som heter Plug &amp; Produce handlar om att skapa system där nya typer av resurser och produkter kan kopplas in i systemet på ett fåtal minuter snarare än dagar i traditionella system. För att implementera Plug &amp; Produce kan multi-agent-system användas, där varje resurs och produkt får sin egen styrning. Agenterna kan sedan kommunicera med varandra för att nå de mål som satts upp för tillverkningen av produkterna. Tanken är att systemet automatiskt hanterar anpassningen till nya produkter. Idag är dock användningen av sådana system extremt begränsad i industrin. En av anledningarna är avsaknaden av mogna multi-agent-system som är lätta att använda och där komplexiteten hos det underliggande agensystemet kan döljas från användaren. Detta är ett stort problem eftersom multi-agent-system tenderar att vara mer komplexa än traditionella system. Därför fokuserar denna avhandling på att förenkla användningen av multi-agent-system genom att föreslå olika metoder som kan underlätta användandet av multi-agent-tekniken för Plug &amp; Produce i industrin.